Automatic image annotation and translation method based on decision tree learning
An automatic image and decision tree technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as incompatibility with image databases, incomplete databases, and noisy data.
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[0035] Given 5100 Corel database images, 570 images of 19×30 are selected as the training image set of the method of the present invention, and the embodiment performs automatic image labeling on the remaining images.
[0036] (1) Segment all images in the training image set to form several image sub-blocks (regions), extract color, texture, and shape features from the image sub-blocks, and obtain feature data x 1 , x 2 ,...,x L (L-dimensional color feature), y 1 ,y 2 ,...,y M (M-dimensional texture features), z 1 ,z 2 ,...,z N (N-dimensional shape features).
[0037] In the stage of discretization of eigenvalues processed by adaptive VQ, taking color features as an example, the first step is to calculate the initial clustering center, let this center be c 1 , and then set the initial number of clusters CN=1; the second step first selects the cluster centers that exceed the L-dimensional color feature, let n be the number of selected centers, if n=0, stop, otherwise ...
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